Early Bubble CPAP Protocol Implementation and Rates of Death or Severe BPD
Bibliographic record
Abstract
BACKGROUND: A multidisciplinary comprehensive protocol to use bubble continuous positive airway pressure (bCPAP) as the primary respiratory support in the delivery room (DR) and the NICU was introduced. With this study, we aimed to assess the association of this change with respiratory outcomes over time. METHODS: Infants with gestational age <32 weeks and birth weight <1250 g admitted between January 2012 and June 2020 were included and categorized into 4 periods, including pre-implementation (P0: 2012-2014), and post-implementation (P1: 2014-2016, P2: 2016-2018, P3: 2018-2020). The primary outcome was the rates of death and severe bronchopulmonary dysplasia (BPD), and the secondary outcomes included the rates of DR and NICU intubation ≤7 days of age, need of surfactant, and pneumothorax. Multivariate logistic regression models accounting for relevant risk factors were used to calculate adjusted odds ratios (ORs). RESULTS: The study included 440 infants (P0 = 90, P1 = 91, P2 = 128, P3 = 131). Over time, more infants were free of BPD (P < .001), and the rates of death and severe BPD decreased significantly: P1 = OR 1.21 (95% confidence interval [CI] 0.56-2.67), P2 = OR 0.45 (95% CI 0.20-0.99), and P3 = OR 0.37 (95% CI 0.15-0.84). DR intubation decreased from 66% (P0) to 24% (P3) in the entire cohort (P < .001) and from 96% (P0) to 40% (P3) in infants <26 weeks of age (P < .001). The need for NICU intubation was similar (P = .98), with a decreased need for surfactant (P = .001) occurring at higher FiO2 (P0 = 0.35 vs P3 = 0.55, P < .001). Pneumothorax rates were unchanged. CONCLUSIONS: In very preterm infants, the implementation of a comprehensive bCPAP protocol led to a significant and consistent improvement in respiratory practices and the rates of death and severe BPD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".